Abstract
Branching Constraint Satisfaction Problems (BCSPs) have been introduced to model dynamic resource allocation subject to constraints and uncertainty. We give BCSPs a formal probability semantics by showing how they can be mapped to a certain class of Bayesian decision networks. This allows us to describe logical and probabilistic constraints in a uniform fashion. We also discuss extensions to BCSPs and decision networks suggested by the relationship between the two formalisms.
Cite
CITATION STYLE
Brown, K., Lucas, P., & Fowler, D. (2003). Decision network semantics of branching constraint satisfaction problems. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2711, pp. 230–242). Springer Verlag. https://doi.org/10.1007/978-3-540-45062-7_19
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